Environmental impact of food by life cycle stage

Bar Horizontal Stacked

Photo by Jose Guimaraes on Unsplash

Please eat less meat - meat is a very carbon intensive commodity…
— Dr. Rajendra Pachauri, IPCC chief, Jan. 2008

Load the data

Where do the emissions from our food come from?

df = read.csv("archetypes/environmental-impact-of-food-by-life-cycle-stage/environmental-impact-of-food-by-life-cycle-stage.csv", header = TRUE, stringsAsFactors = TRUE)
df

Wrangle

sort and summarize

Plot

Greenhouse gas emissions across the food supply chain

# As defined in imitated view
supply_chain_palette <- c("Land use change" = "#1ea349", 
                          "Farm" = "#a3745e", 
                          "Animal Feed" = "#f36e32", 
                          "Processing" = "#417aac", 
                          "Transport" = "#f04b54", 
                          "Retail" = "#f3ca19",
                          "Packging" = "#bcb0ac")

# Reorder to sort by Food Product and Emission
# Group to maintain stack sort
v1 = ggplot(df_wrangle, aes(x=EMISSION, y=reorder(FOOD_PRODUCT,EMISSION), fill=SUPPLY_CHAIN, group = SUPPLY_CHAIN)) + 
    geom_bar(width=0.8, position="stack", stat="identity", color="#777777" ) +
    scale_fill_manual(values=supply_chain_palette) +
    scale_x_continuous(expand = c(0, 0)) +
    coord_cartesian(clip="off") +
    theme_bw() +
    theme(panel.border     = element_blank()) +
    theme(plot.background = element_blank()) +
    theme(panel.background = element_blank()) +
    theme(panel.grid.major.x = element_blank()) +
    theme(panel.grid.minor.x = element_blank()) +
    theme(panel.grid.major.y = element_blank()) +
    theme(panel.grid.minor.y = element_blank()) +
    theme(legend.title = element_blank()) +
    theme(legend.position = "top") +
    # increase margin for right label
    theme(plot.margin = margin(.25, 1, .25, .25, "cm")) +
    xlab("GHG Emissions per kilogram of food product\n(kg CO2 -equivalents per kg product") +
    ylab("") +
    labs(
      title = "Food: greenhouse gas emissions across the supply chain",
      caption = "Source: Our World in Data"
    ) +
    geom_text(data=total_labels, aes(x=TOTAL+0.5, y=FOOD_PRODUCT, label=TOTAL, fill=NULL, group=NULL), size=2.5, hjust="left")

girafe(ggobj = v1, width_svg = 1280/72, height_svg = 720/72,
       options = list(
         opts_sizing(rescale = TRUE, width = 1.0), 
         opts_hover_inv(css = "opacity:0.2;"), 
         opts_hover(css = "fill:black;")
         )
      )

Plot

adding an annotation layer

# With annotations
v2 <- v1 + 
  #annotate("text", x = 3.5, y = "Fish (wild catch)", label = "'Farm' emissions for wild fish refers to fuel used by fishing vessels.", hjust = "left", size = 2.5, fontface = 1) +
  annotate("text", x = 4.5, y = "Nuts", 
           label = "  Nuts have a negative land use change figure\n- because nut trees are currently replacing croplands;\n  carbon is stored in the trees.", 
           hjust = "left", vjust=0.45, size = 2.5, fontface = 1) +
  annotate("text", x = 4.5, y = "Peas", 
           label = "- Factors such as transport distance, retail, packaging,\n  or specific farm methods are often\n  small compared to importance of food type.", 
           hjust = "left", size = 2.5, fontface = 1) +
  annotate("text", x = 4.5, y = "Maize (Meal)", 
           label = "- CO2 emissions from most plant-based\n  products are as much as 10-50 times\n  lower than most animal-based products.", 
           hjust = "left", size = 2.5, fontface = 1) +
  annotate("text", x = 5.0, y = "Milk", 
           label = "Methane production from cows means dairy milk has significantly higher emissions than plant-based milks.", 
           hjust = "left", size = 2.5, fontface = 1) +
  annotate("text", x = 6, y = "Rice", label = "Flooded rice produces methane, which dominates on-farm emissions.", hjust = "left", size = 2.5, fontface = 1) +
  annotate("text", x = 10, y = "Pig Meat", 
           label = "Pigs and poultry are non-ruminant livestock so do not produce methane.\nThey have significant lower emissions than beef and lamb.", 
           hjust = "left", vjust=0.75, size = 2.5, fontface = 1) +
  annotate("text", x = 24, y = "Beef (dairy herd)", 
           label = "Dairy co-products means beef from dairy herds\nhas a lower carbon footprint than dedicated beef herds.", 
           hjust = "left", vjust=0.75, size = 2.5, fontface = 1) +
  annotate("text", x = 35, y = "Beef (beef herd)", 
           label = "Methane production from cows, and land conversion for grazing and animal feed\nmeans beef from dedicated beef herds has a very high carbon footprint.", 
           hjust = "left", vjust=1.35, size = 2.5, fontface = 1)

# Draw line segment
v2 <- v2 + geom_segment(aes(
    x=4.5,
    y="Cane Sugar",
    xend=4.5, 
    yend="Nuts"
    ),
    size=0.5
  )

girafe(ggobj = v2, width_svg = 1280/72, height_svg = 720/72,
       options = list(
         opts_sizing(rescale = TRUE, width = 1.0), 
         opts_hover_inv(css = "opacity:0.2;"), 
         opts_hover(css = "fill:black;")
         )
      )

References

citations for narrative and data sources

Narrative sources: Our World in Data, You want to reduce the carbon footprint of your food? Focus on what you eat, not whether your food is local, GO

@misc{ritchie_2020_you,
  author = {Ritchie, Hannah},
  month = {01},
  title = {You want to reduce the carbon footprint of your food? Focus on what you eat, not whether your food is local},
  url = {https://ourworldindata.org/food-choice-vs-eating-local},
  urldate = {2021-02-15},
  year = {2020},
  organization = {Our World in Data}
}